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Memorias de investigación
Ponencias en congresos:
Parallel implementation of a hyperspectral image linear SVM classifier using RVC-CAL
Año:2016
Áreas de investigación
  • Ingeniería eléctrica, electrónica y automática
Datos
Descripción
Hyperspectral Imaging (HI) collects high resolution spectral information consisting of hundreds of bands across the electromagnetic spectrum ?from the ultraviolet to the infrared range?. Thanks to this huge amount of information, an identification of the different elements that compound the hyperspectral image is feasible. Initially, HI was developed for remote sensing applications and, nowadays, its use has been spread to research fields such as security and medicine. In all of them, new applications that demand the specific requirement of real-time processing have appear. In order to fulfill this requirement, the intrinsic parallelism of the algorithms needs to be explicitly exploited. In this paper, a Support Vector Machine (SVM) classifier with a linear kernel has been implemented using a dataflow language called RVC-CAL. Specifically, RVC-CAL allows the scheduling of functional actors onto the target platform cores. Once the parallelism of the classifier has been extracted, a comparison of the SVM classifier implementation using LibSVM ?a specific library for SVM applications? and RVC-CAL has been performed. The speedup results obtained for the image classifier depends on the number of blocks in which the image is divided; concretely, when 3 image blocks are processed in parallel, an average speed up above 2.50, with regard to the RVC-CAL sequential version, is achieved.
Internacional
Si
Nombre congreso
SPIE: High-Performance Computing in Geoscience and Remote Sensing VI
Tipo de participación
960
Lugar del congreso
Edinburgh (United Kingdom)
Revisores
Si
ISBN o ISSN
0277-786X
DOI
10.1117/12.2241648
Fecha inicio congreso
26/09/2016
Fecha fin congreso
29/09/2016
Desde la página
10007091
Hasta la página
10007099
Título de las actas
SPIE Proceedings Vol. 10007: High-Performance Computing in Geoscience and Remote Sensing VI
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Daniel Madroñal Quintin (UPM)
  • Autor: H. Fabelo (IUMA_ULPGC)
  • Autor: Raquel Lazcano Lopez (UPM)
  • Autor: G. M. Callicó (IUMA_ULPGC)
  • Autor: Eduardo Juarez Martinez (UPM)
  • Autor: Cesar Sanz Alvaro (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Diseño Electrónico y Microelectrónico
  • Centro o Instituto I+D+i: Tecnologías del Software y Sistemas Multimedia para la Sostenibilidad (CITSEM)
  • Departamento: Ingeniería Telemática y Electrónica
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